[Mlir-commits] [mlir] ba9e65f - [mlir][doc] Fix typos in tutorial chapters

Stephan Herhut llvmlistbot at llvm.org
Fri Jun 12 07:04:30 PDT 2020


Author: Kai Sasaki
Date: 2020-06-12T16:04:01+02:00
New Revision: ba9e65f9dbb198fb4e85aa5a996bac44beeacdd0

URL: https://github.com/llvm/llvm-project/commit/ba9e65f9dbb198fb4e85aa5a996bac44beeacdd0
DIFF: https://github.com/llvm/llvm-project/commit/ba9e65f9dbb198fb4e85aa5a996bac44beeacdd0.diff

LOG: [mlir][doc] Fix typos in tutorial chapters

Summary:
Fix several typos in Toy tutorial chapters.
- Chapter 2
- Chapter 5

Differential Revision: https://reviews.llvm.org/D80909

Added: 
    

Modified: 
    mlir/docs/Tutorials/Toy/Ch-2.md
    mlir/docs/Tutorials/Toy/Ch-5.md

Removed: 
    


################################################################################
diff  --git a/mlir/docs/Tutorials/Toy/Ch-2.md b/mlir/docs/Tutorials/Toy/Ch-2.md
index 1180a9f41bcc..cc5b380a9f62 100755
--- a/mlir/docs/Tutorials/Toy/Ch-2.md
+++ b/mlir/docs/Tutorials/Toy/Ch-2.md
@@ -117,7 +117,7 @@ compiler passes - does not include locations in the output by default. The
 
 MLIR is designed to allow most IR elements, such as attributes,
 operations, and types, to be customized. At the same time, IR
-elements can always be reduced to the above fundmental concepts. This
+elements can always be reduced to the above fundamental concepts. This
 allows MLIR to parse, represent, and
 [round-trip](../../../getting_started/Glossary.md#round-trip) IR for
 *any* operation. For example, we could place our Toy operation from
@@ -134,7 +134,7 @@ func @toy_func(%tensor: tensor<2x3xf64>) -> tensor<3x2xf64> {
 In the cases of unregistered attributes, operations, and types, MLIR
 will enforce some structural constraints (SSA, block termination,
 etc.), but otherwise they are completely opaque. For instance, MLIR
-has little information about whether an unregisted operation can
+has little information about whether an unregistered operation can
 operate on particular datatypes, how many operands it can take, or how
 many results it produces. This flexibility can be useful for
 bootstrapping purposes, but it is generally advised against in mature
@@ -684,10 +684,10 @@ variadic operands, etc. Check out the
 ## Complete Toy Example
 
 We can now generate our "Toy IR". You can build `toyc-ch2` and try yourself on
-the above example: `toyc-ch2 test/Examples/Toy/Ch2/codegen.toy -emit=mlir 
--mlir-print-debuginfo`. We can also check our RoundTrip: `toyc-ch2 
-test/Examples/Toy/Ch2/codegen.toy -emit=mlir -mlir-print-debuginfo 2> 
-codegen.mlir` followed by `toyc-ch2 codegen.mlir -emit=mlir`. You should also 
+the above example: `toyc-ch2 test/Examples/Toy/Ch2/codegen.toy -emit=mlir
+-mlir-print-debuginfo`. We can also check our RoundTrip: `toyc-ch2
+test/Examples/Toy/Ch2/codegen.toy -emit=mlir -mlir-print-debuginfo 2>
+codegen.mlir` followed by `toyc-ch2 codegen.mlir -emit=mlir`. You should also
 use `mlir-tblgen` on the final definition file and study the generated C++ code.
 
 At this point, MLIR knows about our Toy dialect and operations. In the

diff  --git a/mlir/docs/Tutorials/Toy/Ch-5.md b/mlir/docs/Tutorials/Toy/Ch-5.md
index ca59da20d127..0c7273637ca0 100644
--- a/mlir/docs/Tutorials/Toy/Ch-5.md
+++ b/mlir/docs/Tutorials/Toy/Ch-5.md
@@ -76,7 +76,7 @@ void ToyToAffineLoweringPass::runOnFunction() {
 
 Above, we first set the toy dialect to illegal, and then the print operation
 as legal. We could have done this the other way around.
-Individual operations always take precendence over the (more generic) dialect
+Individual operations always take precedence over the (more generic) dialect
 definitions, so the order doesn't matter. See `ConversionTarget::getOpInfo`
 for the details.
 
@@ -336,7 +336,7 @@ func @main() {
 
 Here, we can see that a redundant allocation was removed, the two loop nests
 were fused, and some unnecessary `load`s were removed. You can build `toyc-ch5`
-and try yourself: `toyc-ch5 test/Examples/Toy/Ch5/affine-lowering.mlir 
+and try yourself: `toyc-ch5 test/Examples/Toy/Ch5/affine-lowering.mlir
 -emit=mlir-affine`. We can also check our optimizations by adding `-opt`.
 
 In this chapter we explored some aspects of partial lowering, with the intent to


        


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